Optimizing Drug Safety and Compliance in Real-Time by Using Block chain and Artificial Intelligence for Integrated Clinical Data Management and Pharmacovigilance
Year: 2025
Type: preprint
Abstract: Pharmacovigilance (PV) and clinical data management (CDM) are essential for ensuring drug safety, efficacy, and regulatory compliance. However, traditional methods face significant challenges, including fragmented data, delayed adverse event reporting, and limited system interoperability. The integration of artificial intelligence (AI) and blockchain technology offers a transformative approach to addressing these limitations. AI-driven solutions, such as machine learning and natural language processing, enable real-time data validation, anomaly detection, and predictive analytics, improving the accuracy and efficiency of pharmacovigilance processes. Meanwhile, blockchain provides a secure, immutable, and transparent framework for clinical trial data storage, ensuring data integrity and compliance with regulatory standards. This review explores the synergistic application of AI and blockchain in CDM and PV, highlighting their potential to streamline workflows, reduce redundancies, and enhance global drug safety monitoring. While promising, widespread adoption faces obstacles such as scalability, regulatory adaptation, and organizational resistance. Addressing these challenges through collaborative efforts, regulatory harmonization, and technological refinements will be key to realizing the full potential of AI-blockchain integration in drug safety management.
Author: Darshan Gowda B.S
Institution: Dayananda Sagar University
Language: English
Subfield: Toxicology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4413915646